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A novel sEMG-based dynamic hand gesture recognition approach via residual attention network (2023)
Journal Article
Liu, Y., Li, X., Yu, H., & Yang, L. (2024). A novel sEMG-based dynamic hand gesture recognition approach via residual attention network. Multimedia Tools and Applications, 83, 9329–9349. https://doi.org/10.1007/s11042-023-15748-5

With the emergence of more and more lightweight, convenient and cheap surface electromyography signal (sEMG) snsors, gesture recognition based on sEMG sensors has attracted much attention of researchers. In this study, combined with the sEMG sensor,... Read More about A novel sEMG-based dynamic hand gesture recognition approach via residual attention network.

Data-driven Event-triggered Bipartite Consensus for Multi-agent Systems Preventing DoS Attacks (2023)
Journal Article
Zhao, H., Shan, J., Peng, L., & Yu, H. (2023). Data-driven Event-triggered Bipartite Consensus for Multi-agent Systems Preventing DoS Attacks. IEEE Control Systems Letters, 7, 1915-1920. https://doi.org/10.1109/lcsys.2023.3281894

This paper considers event-triggered bipartite consensus issues for discrete-time nonlinear networked multi-agent systems with antagonistic interactions and denial-of-service (DoS) attacks. Firstly, a pseudo partial derivative technology is applied t... Read More about Data-driven Event-triggered Bipartite Consensus for Multi-agent Systems Preventing DoS Attacks.

MhaGNN: A novel framework for wearable sensor-based human activity recognition combining multi-head attention and graph neural networks (2023)
Journal Article
Wang, Y., Wang, X., Yang, H., Geng, Y., Yu, H., Zheng, G., & Liao, L. (2023). MhaGNN: A novel framework for wearable sensor-based human activity recognition combining multi-head attention and graph neural networks. IEEE Transactions on Instrumentation and Measurement, 72, Article 2514314. https://doi.org/10.1109/tim.2023.3276004

Obtaining robust feature representations from multi-position wearable sensory data is challenging in human activity recognition (HAR) since data from different positions can have unordered implicit correlations. Graph neural networks (GNNs) represent... Read More about MhaGNN: A novel framework for wearable sensor-based human activity recognition combining multi-head attention and graph neural networks.

A CNN-Transformer Hybrid Recognition Approach for sEMG-based Dynamic Gesture Prediction (2023)
Journal Article
Liu, Y., Li, X., Yang, L., Bian, G., & Yu, H. (2023). A CNN-Transformer Hybrid Recognition Approach for sEMG-based Dynamic Gesture Prediction. IEEE Transactions on Instrumentation and Measurement, 72, Article 2514816. https://doi.org/10.1109/tim.2023.3273651

As a unique physiological electrical signal in the human body, surface electromyography (sEMG) signals always include human movement intention and muscle state. Through the collection of sEMG signals, different gestures can be effectively recognized.... Read More about A CNN-Transformer Hybrid Recognition Approach for sEMG-based Dynamic Gesture Prediction.

TMA-Net: A Transformer-based Multi-scale Attention Network for Surgical Instrument Segmentation (2023)
Journal Article
Yang, L., Wang, H., Gu, Y., Bian, G., Liu, Y., & Yu, H. (2023). TMA-Net: A Transformer-based Multi-scale Attention Network for Surgical Instrument Segmentation. IEEE Transactions on Medical Robotics and Bionics, 5(2), 323-334. https://doi.org/10.1109/tmrb.2023.3269856

The ability to accurately and automatically segment surgical instruments is one of the important prerequisites for reasonable and stable operation of surgical robots. The utilization of deep learning in medical image segmentation has gained widesprea... Read More about TMA-Net: A Transformer-based Multi-scale Attention Network for Surgical Instrument Segmentation.

Design and Grasping Force Modeling for a Soft Robotic Gripper with Multi-stem Twining (2023)
Journal Article
Shan, Y., Zhao, Y., Yu, H., Pei, C., Jin, Z., & Sun, Y. (2023). Design and Grasping Force Modeling for a Soft Robotic Gripper with Multi-stem Twining. Journal of Bionic Engineering, 20, 2123–2134. https://doi.org/10.1007/s42235-023-00371-9

To improve the grasping power of soft robots, inspired by the scene of intertwined and interdependent vine branches safely clinging to habitats in a violent storm and the phenomenon of large grasping force after being entangled by aquatic plants, thi... Read More about Design and Grasping Force Modeling for a Soft Robotic Gripper with Multi-stem Twining.

Multi-scale triple-attention network for pixelwise crack segmentation (2023)
Journal Article
Yang, L., Bai, S., Liu, Y., & Yu, H. (2023). Multi-scale triple-attention network for pixelwise crack segmentation. Automation in Construction, 150, Article 104853. https://doi.org/10.1016/j.autcon.2023.104853

Currently, intelligent crack detection is of great value for the maintenance of infrastructure, of which the most significant kind in China is roads. For pavement defects, the pavement can be repaired and maintained in a timely manner with an accurat... Read More about Multi-scale triple-attention network for pixelwise crack segmentation.

ADRC Based Multi-task Priority Tracking Control for Collaborative Robots (2022)
Presentation / Conference Contribution
Fan, K., Liu, Y., Zhang, K., Bian, G., & Yu, H. (2022, August). ADRC Based Multi-task Priority Tracking Control for Collaborative Robots. Presented at CICAI 2022, Beijing

When collaborative robots perform multiple tracking tasks at the same time, the dynamics of each task will interact with each other. In addition, the uncertainty of robot model and external perturbation also limit the performance of the system. In or... Read More about ADRC Based Multi-task Priority Tracking Control for Collaborative Robots.

Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification (2022)
Journal Article
Jin, J., Zhang, Q., He, J., & Yu, H. (2022). Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification. Electronics, 11(23), Article 3969. https://doi.org/10.3390/electronics11233969

Deep neural networks have proven to be effective in solving computer vision and natural language processing problems. To fully leverage its power, manually designed network templates, i.e., Residual Networks, are introduced to deal with various visio... Read More about Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification.

Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images (2022)
Journal Article
Liu, Y., Shen, J., Yang, L., Yu, H., & Bian, G. (2023). Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images. Computers in Biology and Medicine, 152, Article 106341. https://doi.org/10.1016/j.compbiomed.2022.106341

Accurate segmentation of retinal vessels from fundus images is fundamental for the diagnosis of numerous diseases of eye, and an automated vessel segmentation method can effectively help clinicians to make accurate diagnosis for the patients and prov... Read More about Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images.

DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation (2022)
Journal Article
Li, J., Gao, G., Yang, L., Liu, Y., & Yu, H. (2022). DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation. Electronics, 11(22), Article 3810. https://doi.org/10.3390/electronics11223810

The deterioration of numerous eye diseases is highly related to the fundus retinal structures, so the automatic retinal vessel segmentation serves as an essential stage for efficient detection of eye-related lesions in clinical practice. Segmentation... Read More about DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation.

A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network (2022)
Journal Article
Chen, B., Zhang, H., Zhang, F., Liu, Y., Tan, C., Yu, H., & Wang, Y. (2023). A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network. IEEE Transactions on Cognitive and Developmental Systems, 15(3), 1449-1462. https://doi.org/10.1109/tcds.2022.3218718

There are many constraints for a multi-robot system to perform a region coverage search task in an unknown environment. To address this, we propose a novel multi-robot distributed collaborative region coverage search algorithm based on Glasius bio-in... Read More about A Multi-robot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-inspired Neural Network.

A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments (2022)
Journal Article
Chen, B., Zhang, W., Zhang, F., Liu, Y., & Yu, H. (2023). A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments. IEEE Systems Journal, 17(2), 1995-2006. https://doi.org/10.1109/jsyst.2022.3198712

This article proposes a novel approach based on a bioinspired neural network (BIN) for multirobot area coverage search in unknown environments. We obtain the dynamic environment information in the search process of the multirobot by combining the BIN... Read More about A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments.

ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images (2022)
Journal Article
Liu, Y., Shen, J., Yang, L., Bian, G., & Yu, H. (2023). ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images. Biomedical Signal Processing and Control, 79, Article 104087. https://doi.org/10.1016/j.bspc.2022.104087

For the clinical diagnosis, it is essential to obtain accurate morphology data of retinal blood vessels from patients, and the morphology of retinal blood vessels can well help doctors to judge the patient’s condition and give targeted therapeutic me... Read More about ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images.

An Improved Point-to-Feature Recognition Algorithm for 3D Vision Detection (2022)
Presentation / Conference Contribution
Li, J., Guo, Q., Gao, G., Tang, S., Min, G., Li, C., & Yu, H. (2022, August). An Improved Point-to-Feature Recognition Algorithm for 3D Vision Detection. Presented at International Conference on Intelligent Robotics and Applications, Harbin, China

Vision-detection-based grasping is one of the research hotspots in the field of automated production. As the grasping scenes become more and more diversified, 3D images are increasingly chosen as the input images for object recognition in complex rec... Read More about An Improved Point-to-Feature Recognition Algorithm for 3D Vision Detection.

Improved Cascade Active Disturbance Rejection Control for Functional Electrical Stimulation Based Wrist Tremor Suppression System Considering the Effect of Output Noise (2022)
Presentation / Conference Contribution
Tao, C., Zhang, Z., Huo, B., Liu, Y., Li, J., & Yu, H. (2022, August). Improved Cascade Active Disturbance Rejection Control for Functional Electrical Stimulation Based Wrist Tremor Suppression System Considering the Effect of Output Noise. Presented at International Conference on Intelligent Robotics and Applications, Harbin, China

The wrist tremor suppression system designed based on functional electrical stimulation technology has been welcomed by the majority of tremor patients as a non-invasive rehabilitation therapy. Due to the complex physiological structure characteristi... Read More about Improved Cascade Active Disturbance Rejection Control for Functional Electrical Stimulation Based Wrist Tremor Suppression System Considering the Effect of Output Noise.

Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems (2022)
Journal Article
Zhao, H., Yu, H., & Peng, L. (2024). Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems. IEEE Transactions on Neural Networks and Learning Systems, 35(1), 417-427. https://doi.org/10.1109/tnnls.2022.3174885

In this study, we investigate the event-triggering time-varying trajectory bipartite formation tracking problem for a class of unknown nonaffine nonlinear discrete-time multiagent systems (MASs). We first obtain an equivalent linear data model with a... Read More about Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems.

Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems (2022)
Journal Article
Zhao, H., Shan, J., Peng, L., & Yu, H. (2023). Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems. IEEE Transactions on Industrial Electronics, 70(4), 4068-4076. https://doi.org/10.1109/tie.2022.3174275

This paper studies the robust bipartite consensus problems for heterogeneous nonlinear nonaffine discrete-time multi-agent systems (MASs) with fixed and switching topologies against data dropout and unknown disturbances. At first, the controlled syst... Read More about Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems.